Status: Under review (decision pending).

This repository provides the public dataset for the BioArtlas project.

• Goal: Structure the multi‑dimensional complexity of bioart works as data
• Dataset: BioArtlas.csv (per‑work metadata)
• Live visualization: bioartlas.com
• Contact: [email protected]

• File: BioArtlas.csv
• Size (current): approximately 81 rows and 17 columns
• Encoding: UTF‑8
• Delimiter: comma (,)
• Quoting: values that contain commas are wrapped in double quotes

• Artist: Artist name (e.g., "Joe Davis")
• Artwork: Work title (e.g., "Microvenus")
• Year: Production year or period (e.g., 1985-, 2015–2017)
• Gen: Generation/group index (integer category)
• Materiality: Materials/organisms/data involved (multi‑valued)
• Methodology: Methods/technologies used (multi‑valued)
• Actor Relationships & Configuration: Actor relationships and configuration (e.g., Artist‑Led, Multi‑Actor Network)
• Ethical Approach: Ethical approach (e.g., Care‑Based, Relational Ethics, Provocative)
• Aesthetic Strategy: Aesthetic strategy (e.g., Conceptual, Spectacle, Data Aesthetics)
• Epistemic Function: Epistemic function (e.g., Knowledge Production, Science Communication)
• Philosophical Stance: Philosophical stance (e.g., Posthumanism, Ecofeminism)
• Social Context: Exhibition/social context (e.g., Art Gallery, Laboratory, Online Platform)
• Audience Engagement: Audience engagement (e.g., Observational, Interactive, Participatory)
• Temporal Scale: Temporal scale/persistence (e.g., Short‑Term Exhibition, Evolutionary)
• Spatio Scale: Spatial scale (e.g., Molecular Unit, Installation Scale, Global Network)
• Power and Capital Critique: Power/capital critique (e.g., Biopolitics, Commercialization)
• Documentation & Representation: Documentation/representation (e.g., Live Video, Photographic Records, Narrative)

Multi‑category values are comma‑separated within a quoted string; commas inside quotes are part of the value, not field separators.

import pandas as pd

df = pd.read_csv('BioArtlas.csv')
print(df.shape)           # e.g., (81, 17)
print(df.columns.tolist())

# Convert multi-category columns into lists (example)
multi_cols = [
    'Materiality','Methodology','Actor Relationships & Configuration','Ethical Approach',
    'Aesthetic Strategy','Epistemic Function','Philosophical Stance','Social Context',
    'Audience Engagement','Documentation & Representation','Power and Capital Critique'
]
for c in multi_cols:
    if c in df.columns:
        df[c] = df[c].fillna('').apply(lambda x: [s.strip() for s in x.split(',')] if isinstance(x, str) and len(x) > 0 else [])

Explore interactive clustering and 2D projections built from this dataset at: bioartlas.com

• Data: BioArtlas Research‑Only Data License (Noncommercial). See LICENSE for details.
• Code: MIT License (to be added separately if/when code is included)

Commercial use, internal commercial research, and integration into paid services/products/models are not permitted under this license. For commercial licensing, please contact: [email protected].

Proper attribution and preserving the original context are encouraged.

BioArtlas dataset (Research‑Only Data License, Noncommercial). © 2025 Joonhyung Bae. Project: https://www.bioartlas.com

For questions or collaboration, please contact: [email protected]